Redwood Shores, CA, United States of America

Albert Danysh


Average Co-Inventor Count = 7.0

ph-index = 1


Company Filing History:


Years Active: 2020

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1 patent (USPTO):

Title: Albert Danysh - Innovator in Run-Length Encoding Decompression

Introduction

Albert Danysh is a notable inventor based in Redwood Shores, CA (US). He has made significant contributions to the field of data compression, particularly through his work on run-length encoding (RLE) decompression. His innovative approaches have the potential to enhance database performance, making him a key figure in the tech industry.

Latest Patents

Danysh holds a patent for his work on run-length encoding decompression. The patent describes methods to improve database performance by implementing an RLE decompression function at a low level within a general-purpose processor or an external block. The hardware implementation disclosed in his patent produces a 64-bit RLE decompression result, with an example embodiment performing the task in two pipelined execution stages, achieving a throughput of one per cycle. This innovation utilizes narrow-width shifters operating in parallel, controlled by computed shift counts, to enhance the efficiency of decompression tasks.

Career Highlights

Albert Danysh is currently employed at Oracle International Corporation, where he continues to develop and refine his innovative ideas. His work has been instrumental in advancing the capabilities of data processing technologies. Danysh's contributions have not only improved performance but have also paved the way for more efficient data handling in various applications.

Collaborations

Danysh has collaborated with notable colleagues, including Jeffrey S Brooks and Robert T Golla. These partnerships have fostered a creative environment that encourages innovation and the sharing of ideas.

Conclusion

Albert Danysh's work in run-length encoding decompression exemplifies the impact of innovative thinking in technology. His contributions to Oracle International Corporation and the broader field of data processing highlight the importance of continuous improvement in performance and efficiency.

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